OpenAI has developed a range of language models that are designed to perform various tasks, such as answering questions, simulating conversations, translating languages, and generating content.
With distinct features and capabilities, these cutting-edge models hold immense potential for developers and businesses.
In this blog post, we will provide details about how different OpenAI models manage the number of tokens in their processing pipeline.
The table below provides an overview of the maximum tokens that can be processed by various OpenAI models.
Model Name | Max Tokens |
---|---|
gpt-4-1106-preview | 128,000 tokens |
gpt-4-vision-preview | 128,000 tokens |
gpt-4 | 8,192 tokens |
gpt-4-0314 | 8,192 tokens |
gpt-4-32k | 32,768 tokens |
gpt-4-32k-0314 | 32,768 tokens |
gpt-3.5-turbo | 4,096 tokens |
gpt-3.5-turbo-0301 | 4,096 tokens |
text-davinci-003 | 4,097 tokens |
text-davinci-002 | 4,097 tokens |
code-davinci-002 | 8,001 tokens |
text-curie-001 | 2,049 tokens |
text-babbage-001 | 2,049 tokens |
text-ada-001 | 2,049 tokens |
davinci | 2,049 tokens |
curie | 2,049 tokens |
babbage | 2,049 tokens |
ada | 2,049 tokens |
Understanding the token limitations for different OpenAI models is essential when choosing the best model for your needs. By taking into account these token limits, you can better tailor your application to the desired outcome and ensure the best results across a wide variety of use cases.
Here’s a simple tool that helps you estimate the costs of using the OpenAI API for different models.
Also, keep in mind the key considerations discussed above when selecting an OpenAI model to find the perfect fit for your project.